Evidence map›Paper›PMID 40853542›Full record

ReviewLa Radiologia medica2025

Illuminating radiogenomic signatures in pediatric-type diffuse gliomas: insights into molecular, clinical, and imaging correlations. Part I: high-grade group.

Ryo Kurokawa, Akifumi Hagiwara, Daiju Ueda, Rintaro Ito, Tsukasa Saida, Maya Honda, Kentaro Nishioka, Akihiko Sakata, Masahiro Yanagawa, Koji Takumi and 9 more

Abstract readReview
In one paragraph

Review in La Radiologia medica, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors.

Ryo KurokawaDepartment of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-8655, Japan. kuroro63@gmail.com.ORCID http://orcid.org/0000-0002-1186-8900
Akifumi HagiwaraDepartment of Radiology, Juntendo University School of Medicine, Tokyo, Japan.ORCID http://orcid.org/0000-0001-5277-3249
Daiju UedaDepartment of Artificial Intelligence, Graduate School of Medicine, Osaka Metropolitan University, Osaka, Japan.ORCID http://orcid.org/0000-0002-3878-3616
Rintaro ItoDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID http://orcid.org/0000-0002-7971-043X
Tsukasa SaidaDepartment of Radiology, Institute of Medicine, University of Tsukuba, Tsukuba, Japan.ORCID http://orcid.org/0000-0003-4530-7375
Maya HondaDepartment of Diagnostic Radiology, Kansai Electric Power Hospital, Osaka, Japan.ORCID http://orcid.org/0000-0002-5337-3455
Kentaro NishiokaDepartment of Radiation Oncology, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.ORCID http://orcid.org/0000-0002-8272-7603
Akihiko SakataDepartment of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan.ORCID http://orcid.org/0000-0002-3647-7877
Masahiro YanagawaDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.ORCID http://orcid.org/0000-0002-0911-6769
Koji TakumiDepartment of Radiology, Graduate School of Medical and Dental Sciences, Kagoshima University, Kagoshima, Japan.ORCID http://orcid.org/0000-0003-4067-2891
Seitaro OdaDepartment of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.ORCID http://orcid.org/0000-0003-4101-5113
Satoru IdeDepartment of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.ORCID http://orcid.org/0000-0002-6567-6736
Keitaro SofueDepartment of Radiology, Kobe University Graduate School of Medicine, Hyogo, Japan.ORCID http://orcid.org/0000-0001-6132-1623
Shunsuke SugawaraDepartment of Diagnostic Radiology, National Cancer Center Hospital, Tokyo, Japan.ORCID http://orcid.org/0000-0002-5409-7448
Tadashi WatabeDepartment of Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.ORCID http://orcid.org/0000-0001-8658-2395
Kenji HirataDepartment of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Sapporo, Japan.ORCID http://orcid.org/0000-0003-0036-8975
Mariko KawamuraDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID http://orcid.org/0000-0001-9211-4934
Mami IimaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID http://orcid.org/0000-0002-1991-2494
Shinji NaganawaDepartment of Radiology, Nagoya University Graduate School of Medicine, Nagoya, Japan.ORCID http://orcid.org/0000-0002-0214-613X

Funding

Japan Society for the Promotion of Science 25K10905
6 · The paper itself

Abstract

Recent advances in molecular genetics have revolutionized the classification of pediatric-type high-grade gliomas in the 2021 World Health Organization central nervous system tumor classification. This narrative review synthesizes current evidence on the following four tumor types: diffuse midline glioma, H3 K27-altered; diffuse hemispheric glioma, H3 G34-mutant; diffuse pediatric-type high-grade glioma, H3-wildtype and IDH-wildtype; and infant-type hemispheric glioma. We conducted a comprehensive literature search for articles published through January 2025. For each tumor type, we analyze characteristic clinical presentations, molecular alterations, conventional and advanced magnetic resonance imaging features, radiological-molecular correlations, and current therapeutic approaches. Emerging radiogenomic approaches utilizing artificial intelligence, including radiomics and deep learning, show promise in identifying imaging biomarkers that correlate with molecular features. This review highlights the importance of integrating radiological and molecular data for accurate diagnosis and treatment planning, while acknowledging limitations in current methodologies and the need for prospective validation in larger cohorts. Understanding these correlations is crucial for advancing personalized treatment strategies for these challenging tumors.

Indexed as

Brain NeoplasmsGliomaImaging GenomicsMagnetic Resonance ImagingChildHumansNeoplasm GradingDiffuse gliomaDiffuse hemispheric gliomaDiffuse midline gliomaInfant-type hemispheric gliomaPediatric-typeRadiology-molecular correlation

Identifiers

PMID40853542
PMCPMC12605632

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.